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Record W3008198656 · doi:10.5539/gjhs.v12n3p103

Facts, Traditions, and Complications of Skin Whitening Products among Female Students in Sudan: A Cross-Sectional Study

2020· article· en· W3008198656 on OpenAlexvenueno aff
Asma Abdelaal Abdalla, Mafaz S. Ahmed

Bibliographic record

VenueGlobal Journal of Health Science · 2020
Typearticle
Languageen
FieldMedicine
TopicSkin Protection and Aging
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCross-sectional studyMarital statusEnvironmental healthPopulationFamily medicinePathology

Abstract

fetched live from OpenAlex

The increased use of skin whitening products serves as a significant challenge for the health care unit. The progressive use of the whitening products exposes individuals to various risk factors and skin-related complications. This study aims to determine the usage of skin-whitening products among female students at Ibn Sina University, Sudan. It further intends to assess the complications and risk factors that may emerge due to the increased use of skin whitening products. It used a descriptive cross-sectional design following a questionnaire-based survey approach. The data was collected from 138 females (age 17 to 25 years), which was statistically analyzed. The results revealed that 47.4% of the population used skin-whitening products, where 58.8% were aged 20-22 years. It revealed a significant association of marital status (p-value, 0.010) and belief (p-value, 0.001) with the use of skin whitening products. It concludes that increased usage of skin-whitening products leads to the occurrence of various complications. It stresses introducing educational and preventive programs to mitigate the use of harmful products.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.223

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.075
GPT teacher head0.406
Teacher spread0.332 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2020
Admission routes1
Has abstractyes

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